Principal Component Analysis Based on a Subset of Variables: Variable Selection and Sensitivity Analysis

DOI10.1080/01966324.1997.10737430zbMath1007.62517OpenAlexW2053662410WikidataQ58293031 ScholiaQ58293031MaRDI QIDQ4353746

Yuichi Mori, Yutaka Tanaka

Publication date: 23 October 1997

Published in: American Journal of Mathematical and Management Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01966324.1997.10737430

zbMATH Keywords

instrumental variablesinfluence of variablesbackward elimination procedureinfluence of observationsmodified principal components analysisRV-coefficients

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25)

Related Items

Exact methods for variable selection in principal component analysis: guide functions and pre-selection ⋮ A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis ⋮ Variable selection in multivariate methods using global score estimation ⋮ Acceleration of the alternating least squares algorithm for principal components analysis ⋮ Computational aspects of algorithms for variable selection in the context of principal components ⋮ Variable neighborhood search heuristics for selecting a subset of variables in principal component analysis

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Principal component analysis.
• Influence functions related to eigenvalue problems which appear in multivariate analysis
• Sensitivity analysis in principal component analysis:influence on the subspace spanned by principal components.
• Influence in principal components analysis